GAO Feng, Ph.D.
CONTACT

Operating Systems, Distributed Intelligent Computing, and Privacy Computing
1. 2002-2013, Source Code Analysis for Operating Systems and Security Analysis for Large Software Systems
2. 2013-2019, Security Analysis for Network Devices
3. 2019-2021, Distributed Terminal-Edge-Cloud Operating System, Zhejiang Lab Internal Project
4. 2020-present, Open Innovation Platform for AI City Brains, Key R&D Project supported by the Ministry of Science and Technology of China
5. 2021-present, Wide-Area Collaborative Intelligent Computing System, Zhejiang Lab Internal Project
Journal Publications:
[1] F Gao, P Liu, QD Yao. A Methodology for Platform Based High-Level System-On-Chip Verification, Chinese Journal of Electronics, Vol. 12, 200301.
[2] Dong Yang, Tao Yang, Feng Gao, Peiqi Shi, Songtao Liang. The Application of the Edge-cloud Computing System Based on Reinforcement Learning in Large-scale Mask Recognition, 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE 2020).
[3] Peiqi Shi, Feng Gao, Songtao Liang, Shanjin Yu. Multi-Model Inference Acceleration on Embedded Multi-Core Processors, 2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI).
Patents:
[1] Supervised Data and Privacy Sharing Based on Terminal-Edge-Cloud Collaboration, licensed patent, First Named Inventor, Patent No. 202110361878.8.
[2] Edge-Cloud Multi-Modal Privacy Data Transformation Based on Smart Contract, licensed patent, First Named Inventor, Patent No. 202110886663.8.
Dr. GAO is currently working on a project related to wide-area collaborative intelligent computing. The project is led by Academician WANG Huaimin and Professor WANG Xiaoyang from the School of Computer Science at Fudan University. The research team consists of researchers from various prestigious universities and research institutions. The team is looking for candidates to fill the following vacancies:
1. Solution design and innovation for complex edge computing scenarios
2. Architectural design for intelligent terminal-edge-cloud computing systems
3. Research and Innovation in key technologies of edge intelligence, enabling the application of deep learning algorithms in edge intelligence